{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "import sys\n",
    "\n",
    "sys.path.append('../..')\n",
    "import torchdyn; from torchdyn.models import *; from torchdyn.datasets import *\n",
    "from pytorch_lightning.loggers import WandbLogger"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.collections.PathCollection at 0x7f83180f8b90>"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAMsAAADCCAYAAADn9Db7AAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADh0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uMy4yLjEsIGh0dHA6Ly9tYXRwbG90bGliLm9yZy+j8jraAAAgAElEQVR4nO2deXhc5Xnof99otK8eW16RLa8Y21gFLBKSkqVJAySEFjchSW9Cb5ZCLg1tUnpp2qwlaW9DHpJmIU1cmrakWXCKaQhLgEDYChjZEBnLq2xkZMmWJY+1rzP67h/vHDSWJc13zpwzczQ6v+fRY1k658ynmfOe791fpbUmICAgNaFsLyAgYLYQCEtAgCGBsAQEGBIIS0CAIYGwBAQYEghLQIAh4Wy86IIFC3RtbW02XjogYEZ2797dpbWunup3WRGW2tpadu3alY2XDgiYEaXUsel+F6hhAQGGBMISEGBIICwBAYakLSxKqRql1G+UUvuUUk1Kqb9wY2EBAX7DDQM/BtyitX5JKVUO7FZKPaa13ufCtQPsEG2EaANE6iFSl+3V5Bxp7yxa6xNa65cS3/cB+4Fl6V43wAHRBsgrln8DXMdVm0UpVQtcBOx087oBhoQr4MQj8m+A67gWZ1FKlQH3Ap/WWvdO8fsbgBsAli9f7tbL5i7TqVQt26H9AVh6NdReN3FcuAJafgQqDD1NU18rXAGx3kBNc4hyo/hLKZUPPAA8orX+Rqrjt2zZooOg5Ay0bIc9n4P4GJQuh3WfEgEYOgkdj0N8CIY7oXgJlK+BspUQfQkG22F8DEprYf4W6G+W40LFoEdh9DSUrYZwKdT9fSAwU6CU2q213jLl79IVFqWUAv4DiGqtP21yTiAsnPu0H45C1zMQKoCTT0Hs9DQnFgHDhi8SApUPOi7XHR9NXGIRlNbAsmshPiA/q9kaCA8zC4sbatibgY8Aryilfpv42d9qrR9y4dq5hyUkpxtg+BSc+A2MDwJxCJVOfD8tpoICMA56JPFtLOkSbfJ1+iVxCMR7oOk2CFXCknfAhV8MBGcK0hYWrfWzgHJhLblBsq0BE7tHTxP07IWTT0KsGxg/99zxvkyuFBiF+GjS6/dA2w5oe0BUubqvnG0XzXFbJyuJlDlNtEHshMbPQd8RGGpPqDohYCzbqzNkFAYOwXMfguc+KD8qroV5G6H2I3PWSRAIi5tEG6H9YTjxGMQn7xIzqVZ+JWn3G3pVvtofgrL1ULwAFr4NKjdOeN9y3O4JhMUJk9WSaCO07oC2X0L3XmbPDuKEcejfB2NLoHwtDLwqzgNIvCeBsARYRBvhwB2QXwWnnoZ4HNruTxjmU9ghucrICTj6Q6jaApGLxGodaJX3J0cFJhAWEyYH/gZPQvc+ZAfJ5V0kFRq6G6C7Cao2igAd+Q8oWwEV62HdTTklOIGwmBBtEIE5vkMi5EMngdGUp7lLPkaCWbwCRs9AfJip12h4HVsMitBYDB+DrudhpAveeq/Lr5U9AmExIboXjvzLRMwiE4SKYelVsOmLsOtmiO6W6PxMzLsU1v6pBDgPfQtGukGPQUG1OOPKL4CFb4ZT/yMPgPg5WUkuMgZtD8LOG6F0NfTunUjRmaUEwjIdltE+dBJa/tNbQcmfD5UbINYPsSEY64fKtVC5KaHGKBhPFYxUMJa4+ZdeAWW1iVyxAqjadLanylIruxok8XIouew8hHu21wgc2SaCX/27ktMWCEuOYAkIJJ6+OyE+grtqS77kZoWKoaASiqqh8gJYe9O5N7MV2FRhUt/AeUBsIkV/zSemvzEjdYmveiheLH/r6ClZ01iPxIb0mIGAGjI+BB2PQXiB5L3NUoEJhCWZaAN074HOnTB6wsULKyAP8opg4xfkyT9TRNy6mUEEZ7Qz9UvklcKqP5UkS0vIUpH8OtZrRRvg6N0SWO0/BOjElwvEuuCFj8sOU7EJiiKzKrgZCEsy4Qo49TyMdbh3vcJqyK+U7OGqzbDpVvldqhvEunHbfgVDqYQlBEVLRAjTufEs4QlXyA0972I40wCxUShfAQPtMNjs/PoA4/1w4tfQ/itY8GZxNwfCMktIrg/peBzGDJ7iqQiVgArBvEtg4eViLySrVSZEG+DMHonhpFIDw/Mgv8i9oGDtdVOrStFG2PUp6Nkv6hqxc48xYSSxa/fug3mbHS8z0wTC0vIjGOuDw3eK+uXUuC1bBxXrxKDWo7Dg8rPVDLs3cbgCWu/FzF4agdJV9oTRCdEGWPpuqZ9ZfwvsvAHOvOj8ev2HoOn/weEfwPq/nNh1fcrcFBZLxRmOwplGGB+BkVPOr1dcI3lSbgXhoo2y22mTZO6w5Gotu8p7dSZSPyEwkTpYeiUwLu+hKgTd7+CiYzDaIa7uwXY4s1PqbHwoOHNTWFp3QNtD0P1bHKsSAIRh2TXu13/s/ks4/aLo96koXgoli73fVeDcHbJmq+SGla+R1J+RcdCDzq493C7pM9WXQtt9gbBkleSUlY4noOcVnAtKCRSWwvl/5f6HGm2E08+LuzUV+RHR+Td/NTtGcqRO1DHrfe07DH3NEiuKddm/3ngfdDwFi97p/lpdYA4JS6LO5PBtMNTq8CJ5ULoGaj/gTTp6tBH2fH6i/DcV4XKpL8mmNyk5ZmM5MaINcOzn0PGogwvGpIq0+S7fuZXnjrCEK+DYtxN5XTYJVUFks3fJgcmlxmf2YFz7kheWQiw/MJUTo/wCaN4GjGDLcRI7Da98FZZcAW/8gZurTIu5ISzRRjj0Xeg5hO1ofPFyWPRWeNPdniwNEBvqzB44vQtGjpufV1WXGVvFLsmCs/BNcPCb4qyIPm9+jaFjYgf5iLnRGDzaANGXkSecDVQZlK6QGIzX9O6HETvB0BLJHfM7sV5Y+l6oWAPhKnvn9h+ABy+BF26UB16Wye2dJdoIu2+BrhdAD9g4MQQL3wrVl0Pd33m2PEDWOHwyISgmu14YQoUw/1IYavN/daJlwyx7jzx0nvsItsobel6CnoSgZFkly3FhaYDOp7GneuVB2Rqo/ePMqDjRBmlJNGYqzHEoqZHMAPCnGpZMskoWqYP+FnFi2PpM4tD2C4hmt5gs94QlOWP3mGkE3CIfCqpg822ZyYx95n9B68+xbUdVbvR+x/MKy9V++Lv2vJIjXbDrz2HLt7MmMLlns1id5Ft3SFq4KapYymGrL89cCrlJ3tdkwvOkhHc2s/QKCeTaajcXh66nJ0ooskDu7SzDUTh0Jwy/ZuOkPKi6EOZdCMUeT8tIDo6O23A45FVKn+L5WyTGM5uxHmhlG6C/KfXxyTTdLv9moe1S7giLdRMe+5k9QSlYAutvlpr10hpvbQAr6Nh3BPqOYmtX+UC3Z8vKOJbRv+KPoC0ful/BvK/asKQqQca7ZOaGsFg34diAuGBNCVXA7z2cuTc92gC9R6D/ILaCdAVLPFtSVrCM/mhjIkispL7MNAWpexfMv1iyvDPoDZz9wmL18bJ7E4bKYMnvO0ufd0q4QrxBdgQlXAVb/smrFWWXSJ24g5vvErXs8Peh6zmM3p+jP5by59qPeL5MC1eERSn1Q+Bq4JTWOrORsmgDxEbsCUp4AazYCkWLvW8KN7nnmF2DvmrzuQ6HZI9f78Fzhxu17pDYTdHiCd3ez829LbVs3c0SOxp4NfU5egA6nhEvGWTEKePWzvLvwHcBD3NCpiFSD03/iK2n9fk3iX1iNXfw6uaJNkqD8NigZOMOt9lbZ7gK1v2ZfL/3dkldL1klpb6j/aC1dJ0JFUHLf8GLN0JeCRCTEROliQlrkbqJRNIDd0imsJ8EKHl3P/UcNP8zRoHLeA9074dX7549wqK1fjoxTzLz9B6EgRYbJ4QlTlFxvv1SX7u07oDTO2HUQbo6yM5w6jl4+a9hqEV+dvqF6Y+PDSXGWSToHoKer8OBb0DFBVC8COZfNvGASB7Y6pfdJrIJLvwSHPwns0Yd8R7oeBYav+S5hyxjNosnMyWjjdD0VWx1qJ93SWJkQgZsleGTzgUFJDeq+UAaCxgSwzmO7EZngBPPQOVq6RkWKobOJ6BsbfZ3FwtLJVv/V7Dnixjl8433wMHviLPAw5SYjAmL1nobsA1kTJ4rF91727nDRqclJE2s134icykiLnUQchXdA90vyRdKegb0H5dGfL4QlqSHWMt/Qu8rZufFzsCpp7xbF7PVG2bp2h3/g7ENUHweFFdL8zkveX38xMOJsmU/k7B54iMyJq9lO6z+qH/mTNZ+GPb8Dcaf8cBxTx02s1RYEkVSYyaBupCkiJQuh5XXe740WndAy89kctZsY+AA7PlrIB/m1SWCtFkUlk23Qut/iQppQijsqf3lSm6YUuqnwPPA+Uqp40qpj7tx3WkJV0jXRBN9tmozLLocVv2Jtx6TaKM0wT78g9kpKGcxBmd2we5bxQuXTeZdBPkLzY6N90gT9+a7PKl/cUVYtNYf0lov0Vrna63P01r/qxvXnZaepglVYUaKoeQ8KFyYmZ5arfdLW59cIX5Gdpr718Jj7xSPU6aLsIoXi1YQKjQ7vvn7MHRKPg+XmV1Zx3tvh/tWSGM2k7SIggqZ+V682JutOdo48RQLV0hz7Vykvxk6H4emf4AnrxbbJlPUbJVeA8U1hieMSNxtOOr6UmaPsEQb4cj3ZXa8URS8EPLnebympDjFycfJ/TF5MYmYtz+QuZeM1MH5nwHiknlhwngfdD3j+lL8b+Bbnq+BVsgrA204BqF4ESx6Cyyo904FC1dI9LhkGZxw0vbHKSFYc7P0Fnvt5zLLXo2LuhkfgVEHHWxM0cNS2ZmBIODrWLbmq3dD104YM4hdxRw2+5uBWSAsiaf38EkYtJF6X1rr/UzDWK+oeCd+PRFhd5tQmUwFPu+9knkweQb94ndM5IZZWQnDUTjxIIz2Shyl7wDE+3Ft5+trggPt0PmsPCgyMdGr9jr5+1p3iDqYSg2PNrruRva/sFgRXVtjQvJh0dsy0/u37WEYPOr+tefVwxv+JXXu1uSO99ZxVvlu812SE9b1nPx/+LQMaUpXcOJn4NQTULhUZlhmoro02pBovl4IOoWwxE7Do5fBpi+71jV0FghLIqI70Jp4OqYiDxZc5n01YbQRXrgButPoIn8OYVjwJhF0S8VJV+Cth83mr8r/ow0Q/vTZ+WbpMNIOg8vgueu932Gsv2X1J6D5W6mPHx8SOzfduTUJ/C8sMNEuyCQHrGyV900NrBqa7t0uXjQkpc1ur32ywFnfWyrNqWeh8xkZxacN+itPRd9BmWF58JtyXa/e++SiseZ/AQzskrwy1wKVs8MbFm0AbZgsWbTI27UAHPqeNLC2k8A5E8UrZArWG/8tcxHzSJ10iPn9xycai5t6myYT74Xj94md6EF84xyiDVBYYXbswGuilbgQH5odwhKugNZfpD6uYDEsucr7D6x3vxQppUvBfKj5Y7jw87DlO9lLLdl0K1zxPFx6pzgUHBGDtkfh6I+8j8NE6sXpgUGgMt4DJx4TTSBNgZkdwtLxOIylCjIpqH4TFHscrd97e6JWPM1dpXwD/N7jcPmPJbnTDxm/tdfBpi9A5YUyzsIu8Sj0H/Y+DhOpk4dL9RvMjo82QPn6tB+i/haWlu1iOLY9QmrvTb6kmXt947X8J4yl48MPQeVF8Oaf+ENAJrPpVnjPHlh8pbid7TJ8AgbaMpMas/BthgfGXXmI+tfAtwq7hk7DaHvq40Nh7z1gLdulMtNOr96zCEPlZljxPn9VJ07F4FEpax5zkMLT+QSgvc1attzIefPEjT0jeaLKp7kW/+4s0Qbxp5tGo8NOdW0bHL4TZ4KS2E0u+3c472ooqvZ/j+Jl18L4AJDv7PzOFzzJz3qdSD3Eh6BircHBMWj6Wtov6V9hidTLrMQ8Q93ZatnqBVbCZM9hZ+cv+0PY+Fn5cGu2+sdGmYlNt8LGLyaaXji5TYbgtXvcXtUEkTp5H4uqMWoD23Mghw38SJ30hFIGkeZQERR4mDRppdwYlQVMomAJvPVeMZ5ng5Aks+lW+INmEXYndL/kfT1M9Vukl0AqwuEcN/CbfwAxg608rwLOu8Y7m8Xa8rFp8OaVwcLLPFlSRrnwi867Yh69y921TKYoAqs+lvo4nSdjCNPYXfwrLC3b4dSTZsdWrpcAm5dP7Vd/CnHDTi3hChmvV7ZmdkznSkWkTtqlUmT/3P7D3u4ukfpEU74UMZd4H/QeTive4l9v2Kt3Y5bsF55oROcFVmpL57OGJ4TgnUmjEWZ7x3uLlddLWkt/s/1zD31LVFgvUvojdZL5nDLuFYPOp2DsIvlsHKzDn8LSsh2ihnlXIQexADsc/l5iEKihF6zsgsz2T84UVor8r7ZgVKWazHBUWq165UouWmyWicz42U0IbeJPNaz9AcgzFIL8Cm8jxj37YNDGhKqKld6tJdtE6qDASe7dsKQIuZSjdQ41W0EZ3srFKxzv9v4UlopNMGrqeQp5O024aCHmvclqM9rVPStUrMZR7GX0ZMJ960HeXqQO4ylipcsc727+FJaBI+bbZbjQ2xqKwgUYv02rrhdVJZepWJ9w0zsQmLYHvQvGFhqODQ87yHlL4E9h6dmPcaJimcc350gXxjvL8fuzOvMwI6y7Cc5zGHdR2jtbbtm1QF7q447/3HFWtD+FpeICwCDQhJI2OV4ybNDJ3aLvSGKSVQ4TqZMmIHaNfJDKxQc3u+9KjjZC98sYqWLxkcScHPv4U1jKVmPmfdLOMmNNiDZK5uywaSKhkmTO4sXerMdPROpx5kjVMNYrc2bcJNog1zXSAPKgaKmjl/GnsPTuxewPD0lavhdEG6TAK1xieEIeLHp77sRVUlHsMKI/1JlQmVwkUg/lqzAS4HChdMRxgP+EJdoI3QcwauVi9cD1wh0ZqQfyZECQCaFSyQHLtfjKVEQbEqqyg9vHtO+bHSJ1sPQqqNqQ+tihDgl4O7hn3GoMfqVS6qBSqlkp9dm0LhZtgJETZsdWrpMeuF65I4sXy5BPE8Z7stMLOBtE6iHWAxUGN+c5jMO+r7hfehyuMHywjYLKd3TPpC0sSqk84E7gKmAD8CGllJN3UYjUQ4Fh44TiJdJAzit35NBJySkyIg+692SmYUO2sVqq9hsMSp2K2CC89Bl3BaanCSMPargK5m12dM+4sbNcCjRrrY9qrUeBnwF/4PhqkTqofqvBgWEYPDYxTNRtoo0w3I6ROxJAFUP/EXnCzQUqzk8UhzlhXN4ntzMvxg3s3PxKx0m3bgjLMiA5H+R44mdnoZS6QSm1Sym1q7MzhTu28wmDl9Uw7w3elq2WrsTYRaqHYfkHpb3qXCDdeFLFGnczLyo3wpCB+j6aqgR5ejJm4Gutt2mtt2itt1RXV09/YLRR5tqnRMHgEdfWdw6ResPJYgnCld53lvEb6eyim7/qbuZFTxNog3BDKOzYrnRDWNqA5OEZ5yV+5oxoA1RuIPXSYhLp96pHVaROctRMCRX5Z+Kv11g326J3Or/Gk3/ogTPEIChZusqxXemGsDQAa5VSK5VSBcAHgfsdXy1cIbaISe5R5GJvM45794IyjLOMdc0N4x4mOqssu8r5NYbb3H2/arbKAysV/YccN9JIW1i01jHgU8AjwH5gu9badN72ufQ0id5vUlMfG/Qu4zjaKHX32rB1v7WzzAWsMusTv0njInF3nSGRukTsJ9XLxiSDIFtxFq31Q1rrdVrr1Vrrv0/rYsMnYTwGowb2QmHEuyzfaAMsfIsMRTJCJ3qKzRHafgWtP0vjAuMJd6+LxAzc/EpB1SXZibO4TtFiKKnBSP8c6vBO9Xm9SYXhzhLvhRc/mdl5i9ki2uDOjJf2h11YS9Jcz5FU6lW+9Jcump+1OIu71GxNRIYNPBtnXvau+i5SJ2rCiGGTChC1MJPzFrNFpF5G8qXLmZfTv0a0QaYTH7gDdCrhHZOdBbIWZ3GX3oPQs8fs2PG4d+kuIDd+2SobJ4zb86DNViJ1sPwDLlzIQZr/ZCL1cPp56N4v075SMdQOp/7H0Uv5T1jaH4BwOUbesFifjH/zyrBeejXkl2KrBVDXM7mfH9ayHV75sgsXKkg/ny5SB/MuhpEOjFVmhyPY/ScsS68WIZhn8oQeMzPqnFJ7HdR/HwrKDU8YkwlauexCjjZC4986nxJ2FqNw4FvSQceyO5xQuRHyDGa1gAQlV3zY0cv4T1hqr5MkPdO0hNFeb0t5I3XS+d6UjqekIV+u7i7RBnfHZsd7YLBN3PROHzKxXlj50dTHhSMy7MrhQFb/CQvIH59v2Lt4tAu6957tFXGb8tUYv1WxMzKjMddq8a1ZOdG9MObybl66RjyPTtXpSL2kGqVS3fMMk2KnwZ/CEqmHcZP8MMQro0cnmnd7oQIpsNfneAyO/zJ36luijTJcNT4CbTvMPxtTBhx0uZzM4W3A2MzHxGOJVq/O8KewAFQbNtTuOSC9uqy4iBfGftFiKFth75zRqJQl54L9Em2QQN7ga4mpZyluSrt0vwJnHNYCRRuh8XNwxuDc/PK05vj4U1is6LkJOqE/W/M6vEhkrNkKKz4AoUrzc4aOwYnHoSu9zu2+IFIP839HbEnTMmvAuBZoPJbwgjpIf4k2QP9Rw+UUwrpP2X+NBP4Ulkg99B4yP/7Vu71bC0yMwd70t9h6y0Y6YOTU7N5doo2y/uGoqGIms+ct8krNjhtph7J1zmqBwhUSmE6JEg0hjbIAnwpLnTSRNn2S9x7JzNO7KAI17zc/fnxIujB6OS7Oa1p3QNcLsOdLcPoF8/Pyl8Bi0xR+Jd357arQ0UbpAWZUsRmCkMORfxNX8CnhCiiZoUgsmZE2OPQ9b9cD8mHmFWDcVxeAsdmfAtN3FLDZlaVqgwxBCpmoVhpGeuyr0NEGiA1gFIwMFYgDKA38KyyxXinUMVlibBBO/cb73SVSlygJsNnYr+vF2ekZizZKFni3zRyu/PkQLkp0yDF84MUclPvayd0bHxebJScnf0XqZWpUvkkj5zgUn5cZ2yDWCzV2e/2OwP6vwyu3ebIkz2jdAa/tsFdeTQhKlsqsR4DVN+DZbdbTZGivICqYHk/rHvGxsNTBkmtg3HD7H2rPTGeVSD0seSes+Qt7540PSQ3IbNhhrADvsXulAtSYMGz8PGz4a7HvQKLlNR80ODcOT/2Rvfem7Vfm0xYK58uwozRCC/6c/GVRWAnFS6UUNBX9R90vJpqK5KlePS9D59M2Th6Eptvg4Hfh0n/2dlRGOrTugMN3wahhg0GLmuvEzR5tOPumHDR07bbdL+14U9kulofO5L4ACM+HJVfIBIA0Qgv+FhaQXsOqyKDt55ikvWSSJe+xKSwJYlHY94+i0vmhyYV184UrRFXsc/LQKYXLfyzfTv57ll0rk4JN5j4eSxTPzTR/0qphMS35vuAvE5130nuf/auGgbxhy65JFBoZeKA6fpPZSsX4gIxdc0L3y/DSZ2HXzbJmr/LaTLBShfZ8yaGgAAvfMP3vNt0KNYb1L7H+mTMfoo1ip5x+XtJvUhGe51qLKn/vLJbKM3RScq1GUzRRi52RDzyTT+zIRRDVMPSa/XNjpyWG0f2KjAEv+YX008r0TjMchSPbZOKaE0IlUP27Mx8zeBQKF8NIivk1w6cg+jIsftfUv482wPDpxMCrFNpGqBSq3+TaveDvncVi3U3SwdCE/qPeJVROpmYrLHsPXPT1iY7+thkTI7V7F3Q8mVmP2d7b4f51sOfvnAsKYVhyZepRG8uulVqflIxCX/P09me4Al67BwYMHk6F82HBm1y7F/y9s1hE6qDANC9rFDqeFgHzmmRjv78FDnwDRjucXy/eL1m9P18K4Xx5Iq64zv2d0rJR9t1uVoo7HYWLRU1+4w9SH7vpVvGQ7b5FmnvMRLxXgsxT2S09TYl6GoNkzsgWV7uEzo6dBSSzOGTY8K7tvsy3JSqKwCV3QMh5VuvrjJ0Qta7tXnj+o3Ds5/Ds++DRt8xsk81U02P9bu/tcq0X/zw9QSEMdV+x91CK1JvfuGOnpQnF5L+lZ69hlWYYiha4mlw7O3YWEDfrsXug7ZekfKqMdMlIA+u8TBCpl6f1pi/A0R/CYDuMu1AkpQeh41H5vr8ZunbCkX+D+KAYw7FhGOuE/GqpMymtEQM4Uic3mlWE1r0XOp9PbfcZEZbER7tE6mDlB8VO06nyuRT0H5f1Wzd7tDHR2M/EC5YHw3ZiRKmZPcIC4hDLK4R4qi1YS91F+wMZFJYklWzpFSI4jbfBiGGE2ZhR6PjVuT8e6QRVCoOtkstVuVHUtwPfhridCHwKyjfA8vfJ95ZtaOfJHa6QngYjqYRlHPr2QeVa+e/e2+HQtyBumBaTX2LWKNwGs0tYxkehIAJDw6RsoxPvlvmFXpEcm3jtHokj5JVA1UZZZ+lKUIbjyd3CeloPvwbPudGqaBKbvzZRv279/XbtgVgvFC2S0oVUTfpGTk9sIofvTMzLMaTyQlHdXWR2CUvtR4AfiX/dxJDufEo+VNvZrEnqi+XlsQSjp0n05r7D8vTuaZIJWPERGb82fErmvXc8LQZ7rpAfmUhhgbN3UjtE6mHBG0R9HEhlVyb6Eu9dbRZTsShdB+96yv7aUpCWsCil3g98GbgAuFRrvcuNRU1L7XXytfNGyVtKZaCOD6VWE5J3iJ4mOPWsjN4LV8pk27YHoHsf4tMvgLyiCW9OzytnX0uPudv5xDfkw8K3u+NVitTBGxLes4cultGCM0X2R07Dni9g3JAvVCqOBw9Id2fZC2wFDHyHLrLoHRKU6tpJyjavDbdI0G2q9jfRRtjzeRgbgN79YjC/vhu0I0ZSsjE5CnF39WD/kifjCvWotNM1cQ/bZcNnxREzfILpjfZxjFr5Wqz6hKh6TjSKFKQlLFrr/QBK2SmGcoGeJtFfVSi1Y0T3wp4vyrxHK5HOUrPOvARn9iWi7zHO9aQb5h7lGqFiUXkXv0OcJA7nxqek9jrJBWv7b4yGp6aibD1ENjlzPBgwu2yWZIqWS9pDzCSFfwSObhOVqmg+lK+F0y9LU4mzjMw0u8LnAqoMVv4xrL1JbrglV3g7J7NqIwwcS6hj6ezaiUpIy4XvQZeflMKilPo1sHiKX31Oa/0L0xdSSt0A3FVugS4AAAv4SURBVACwfPly4wVOSc1WiSeEPwk7b4K4YXBtpF1yk3oOkt4Hk2sooAQqV0k9SrK73aMb73Wsz7Lt4cQO4/CBFS6B+fXOHQ8mL5HqAK11GoMDz7rONmAbwJYtW9LTb5LfkGPbJdJtjE0dOKcpgupLoXw9FC8+N73EwxvvnNc43YDznT0fll/neYrT7FXDLKo2Sif9ETci03OBMBQvk3jVgnpRt7JdTwPSpig831kKzrL3euOAmES6ruNrge8A1cCDSqnfaq2vcGVlplhxkKZ/wJV5H7mIKoFwgQRKN3zWnxWaNVulHqnrGXvnqRKprswA6XrD7gPuc2ktzrC28d5maP2JixcOcbZaEAK0DFotXAIFpVC0TFLb88pkotToGZm0rAqk9U75OkklDynQIYnsxwZ5vcHGaFfqDNxpyYeytZLeMp5oB6SKoKBCmqqP9UPRPHH7Dh6Dpe+VDFy/CUpynMs4szxBuArKVqYuD3CJ2a+GWVz+Y3hqWFLcbRGSm6xyAwy1glYyTUxpaXAw2gN5iXym4sWw5dsTakvzXeKBiQ/Jh93+AISvkbLhik0S8Z4ptT7aCHtvk677+dXAqJw31ivu7LwKqL4cBo/AQLtUZsYHAS0pI6F8WPV5aP+luNHX/plc9+A3JRZVND/hCKmYSPP3G1aVZvsDMr3LDoveDlUXZkyNzB1hAWnq1vYQthrC5VfBordBuBRqrpWn75pPyI184A4xfq1s3sk3frKbMlJn/6kdqYO33Hv209W6qa2bKD4El/7TRGxo6KREtceHYeX18pqTA64V55+9Lj9j/a3xuDwUTKnYDMvendEHgNKmRf8usmXLFr1rl0eZMdFGePxdMGZjFFrpOlj8NjEykz1CycmCmb7psvnamSTaKIVeR7eZn1P9dokFrfmE68tRSu3WWm+Z6ne5tbOA3FiLfheO21DHBg5B+4gE4KwSVMsWytaNms3X9pLkRuNdz0DPYbGpjCmEhZdnRaXMPWEBqNwEnc8m0sANGTom3RcXvUXUnbnwVM8G0QY48Wto+4VMm7Y766Vqo0w0yAKzp6zYDjVbpdtIvmGfXYtYF+z+v1JV2PVC7o268wOReuh4ItFp1I6gFEDRUul2mSVyU1gidbD0KrjgM/Zr4kdPiJOg4xlpih3gDtFGePqP4MmrYdRBUV5pDVz8zay6vnNTWECeYEXVsOrjgN1RA8My57C3ObvN73IFqxSi/VEYPm7//PxquPzerMeIctNmgbMN5DUfhSffC8N26uHHofPJxBRcAtvFKS3boemr0HMUMBk6NImqLbDuRl+8/7krLMlYalnL3eZd+QEYh9d+BiefkhiI36LffiPZ3d17UAKNnS9KloGd8XoW8+rlc/NJMDV31bDJrLtJ0lPsDiICsWOe+zA8dKnsUJnspzybSB6v3v6A1M0PHJwYkmuHsgtg7Q3i+fLBrgJzZWcBecN/5x/g0HclX2uoHXvemDHoboDuPEkn72k6u5lF4GaeiMYPR6Ht19Is0Aml62HF+32zo1jkXgTfhOeul5Hb/YdwXkMRlqTKirVQ877pU2LmGntvhz2fw1kGuIKq34E3/lvW3sO5FcE3YenVMBKVtkUxp5OEYzDeL51fip+DyCWe1X77jsk9ww5/D3r2weAJe/ldkyldK7UpPn3/5qawWC2VXrgRoi9C37FENq+N3lSvMwInHpKM2dLzoGJ97u8u1jChA3dI58+Ox6UzjuN6ohCUnQ8VqzOWbu+EuSksFutugmi9eLqO3SMN3Rx1dNEwdFTqSgrnT+SX5aItE20Um+21/4axKGkX3BXXwtr/k7qcwQfMbWFJjsW0PwBVF8FAS+ImcMBIhwhc2y+AQqi5Rn5uuVFNalz8Rst22Pc16aVctERaSo1FSb9NVEhcw5Xrpu7p5kPmtrAks/RqqXSMbJEqw7SqLseBIWi9B049LUVkRYuh/SFY/qGJw/y080yuqbE6dLbeJ7NnxgekOC5t8mXs95J3Qe9eed9nCXPTG2bC3tsTbUPd7AQTAsLiPcvLk8KzsW5Yf0v2BCa54eD8y6B5G4yeBp0HjIqXz61+aqFyydfLUtawCYE3zAmbbhWV48QjiWZ8bpBow9T6EyhZCWN9UhabPINkKrwoBLOuOdAKZ/ZA7+FEM3OPGuqFymDlh3xtwKci2FlmIlk1efGTMuDVE8Kipq27eWK2S3LKyNggFFaBypPjYOqKTkt1gon5LMnXsWym4ajYViUrREBcGXA0DXmV0r9gybsz0q4oXWbaWQJhMaVle6KJdSe2C5bsULQMxsdk10keB1e4WPoElCwX26pkmdTg9zSJChUug9M7E+bSSSAmkwDySxBjPJzYIa2uNXne/h3kw5qboDDRsWWmufY+IlDD3MBKonz1bug7CCO99ur8TRlum/rnIyclDGRNFe47LOMxQmHpBsMY57RvinVN4dkdn/Svy6giyC+H5R+QJt0e1Mlni0BY7GAFM1u2i1rTcxDOvJidtYwn0t3Paj6fzcbmRVBaK+9PsgqYQwTC4gRLaCxP0rGfwMBx0HbS/3MFBcXLYdWfzBpVyymBsKSDFdSs3CjZzMOdknPmRmTb7+RVirq1+mM5LyQWgbC4gbXTwMRu0/ZLmRoc78nu2tyieAWUrYGe30rjiPxSOP8zc6ogLt3G4F8H3otE7o4AH9VauzhHehZi7TY1W6HhkxAuF49VuBwG2yVTedZMFAsBBZBfDKXL4ZI75Md+yjzIIGm5jpVS7wKe0FrHlFJfA9Bap+xVMytdx05o2S59h0tWSJ/ioqXy8xMPJ9y7Xrpu7ZInzcxLV4p3TYVgwWWy7nkXzxlVyzPXsdb60aT/vgC8L53r5Ry1103dd7hlu7igQ0WSpdx3BM7sToyj89qjVSjuZsubRgjyyqF8JUQunQgczpX2sTZw02b5GHCPi9fLDaZqw5ps41hEG2HXzRDrk5nz4WIpfR48kRCifHnaE5cis9LlcKYJaQShkN4CiZ0qVA6hkIy3yC8Vgay8UEaR55XDivdJcmTvAUBLMqOVDT3Tuuc4rsyUVEpZdaQ/nuE67s2UzEUidbDlO2c/zS1nAUyoQcljLpJr3ruegcE2KF0BVZvl+Fe+IqXTKz48kQZv7RhL3x0Ig03STndRSv1v4EbgHVqbtfGYMzaLF0ylHlkC1PJTmSFTvMzXmb1+xjObRSl1JXAr8FZTQQlIk6nUI2uHWXl9TkbO/UK6Nst3gULgMaUUwAta60+mvaoAewT2RUZI1xu2xq2FBAT4nbnTkTIgIE0CYQkIMCQQloAAQwJhCQgwJCtlxUqpTmCmLhALgK4MLccOwbrs4dd1wfRrW6G1nnK+YlaEJRVKqV3TBYaySbAue/h1XeBsbYEaFhBgSCAsAQGG+FVYtmV7AdMQrMsefl0XOFibL22WgAA/4tedJSDAd/hWWJRSX1dKHVBK7VFK3aeUqsr2mgCUUu9XSjUppcaVUln39CilrlRKHVRKNSulPpvt9QAopX6olDqllNqb7bUko5SqUUr9Rim1L/EZ/oWd830rLMBjwCat9WbgEPA3WV6PxV5gK/B0theilMoD7gSuAjYAH1JKbcjuqgD4d+DKbC9iCmLALVrrDcAbgT+z8375Vli01o9qra3mWy8A52VzPRZa6/1a64PZXkeCS4FmrfVRrfUo8DPgD7K8JrTWTwNOh3V6htb6hNb6pcT3fcB+YJnp+b4Vlkl8DHg424vwIcuA5AlDx7Hx4c9llFK1wEXATtNzstpkz636/mysK2D2opQqA+4FPq21Nh5Ik1Vh0Vq/c6bfJ+r7r0bq+zPm4061Lh/RBtQk/f+8xM8CpkEplY8Iyo+11jvsnOtbNSypvv+aoL5/WhqAtUqplUqpAuCDwP1ZXpNvUVL7/q/Afq31N+ye71thQer7y5H6/t8qpb6f7QUBKKWuVUodBy4DHlRKPZKttSQcIJ8CHkGM1e1a66ZsrcdCKfVT4HngfKXUcaXUx7O9pgRvBj4C/F7invqtUurdpicHEfyAAEP8vLMEBPiKQFgCAgwJhCUgwJBAWAICDAmEJSDAkEBYAgIMCYQlIMCQQFgCAgz5/2bZpRv9s/mxAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 216x216 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "data = ToyDataset()\n",
    "n_samples = 1 << 16\n",
    "n_gaussians = 7\n",
    "\n",
    "X, yn = data.generate(n_samples, 'diffeq_logo', noise=0.05)\n",
    "X = (X - X.mean())/X.std()\n",
    "\n",
    "import matplotlib.pyplot as plt\n",
    "plt.figure(figsize=(3, 3))\n",
    "plt.scatter(X[:,0], X[:,1], c='orange', alpha=0.3, s=4)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "import torch\n",
    "import torch.utils.data as data\n",
    "device = torch.device(\"cuda:0\" if torch.cuda.is_available() else \"cpu\")\n",
    "X_train = torch.Tensor(X).to(device)\n",
    "train = data.TensorDataset(X_train)\n",
    "trainloader = data.DataLoader(train, batch_size=512, shuffle=True) "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [],
   "source": [
    "from torch.distributions import MultivariateNormal, Uniform, TransformedDistribution, SigmoidTransform, Categorical\n",
    "prior = MultivariateNormal(torch.zeros(2).to(device), torch.eye(2).to(device))\n",
    "\n",
    "f = nn.Sequential(\n",
    "        nn.Linear(2, 32),\n",
    "        nn.Softplus(),\n",
    "        nn.Linear(32, 32),\n",
    "        nn.Softplus(),\n",
    "        nn.Linear(32, 2)\n",
    "    )\n",
    "\n",
    "# cnf wraps the net as with other energy models\n",
    "noise_dist = MultivariateNormal(torch.zeros(2).to(device), torch.eye(2).to(device))\n",
    "\n",
    "cnf = nn.Sequential(CNF(f, trace_estimator=hutch_trace, noise_dist=noise_dist))\n",
    "\n",
    "nde = NeuralDE(cnf, solver='dopri5', s_span=torch.linspace(0, 1, 2), atol=1e-5, rtol=1e-5, sensitivity='adjoint')\n",
    "\n",
    "model = nn.Sequential(Augmenter(augment_idx=1, augment_dims=1),\n",
    "                      nde).to(device)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Learner"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [],
   "source": [
    "def cnf_density(model):\n",
    "    cnf[0].trace_estimator = autograd_trace\n",
    "    with torch.no_grad():\n",
    "        npts = 200\n",
    "        side = np.linspace(-2., 2., npts)\n",
    "        xx, yy = np.meshgrid(side, side)\n",
    "        memory= 100\n",
    "\n",
    "        x = np.hstack([xx.reshape(-1, 1), yy.reshape(-1, 1)])\n",
    "        x = torch.from_numpy(x).type(torch.float32).to(device)\n",
    "\n",
    "        z, delta_logp = [], []\n",
    "        inds = torch.arange(0, x.shape[0]).to(torch.int64)\n",
    "        for ii in torch.split(inds, int(memory**2)):\n",
    "            z_full = model(x[ii]).cpu().detach()\n",
    "            z_, delta_logp_ = z_full[:, 1:], z_full[:, 0]\n",
    "            z.append(z_)\n",
    "            delta_logp.append(delta_logp_)\n",
    "\n",
    "        z = torch.cat(z, 0)\n",
    "        delta_logp = torch.cat(delta_logp, 0)\n",
    "\n",
    "        logpz = prior.log_prob(z.cuda()).cpu() # logp(z)\n",
    "        logpx = logpz - delta_logp\n",
    "        px = np.exp(logpx.cpu().numpy()).reshape(npts, npts)\n",
    "        plt.imshow(px);\n",
    "        plt.xlabel([])\n",
    "        plt.ylabel([])\n",
    "        cnf[0].trace_estimator = hutch_trace\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [],
   "source": [
    "class Learner(pl.LightningModule):\n",
    "    def __init__(self, model:nn.Module):\n",
    "        super().__init__()\n",
    "        self.model = model\n",
    "        self.lr = 1e-3\n",
    "        \n",
    "    def forward(self, x):\n",
    "        return self.model(x)\n",
    "    \n",
    "    def training_step(self, batch, batch_idx):\n",
    "        # plot logging  \n",
    "        if batch_idx == 0: \n",
    "            cnf_density(self.model)\n",
    "            self.logger.experiment.log({\"chart\": plt})\n",
    "            plt.close()\n",
    "            nde.nfe = 0\n",
    "        \n",
    "        x = batch[0]     \n",
    "        x += 1e-3*torch.randn_like(x).to(x)\n",
    "        xtrJ = self.model(x)  \n",
    "        logprob = prior.log_prob(xtrJ[:,1:]).to(x) - xtrJ[:,0] \n",
    "        loss = -torch.mean(logprob)\n",
    "        \n",
    "        nfe = nde.nfe\n",
    "        nde.nfe = 0\n",
    "        \n",
    "        metrics = {'loss': loss, 'nfe':nfe}\n",
    "        self.logger.experiment.log(metrics) \n",
    "        return {'loss': loss}   \n",
    "    \n",
    "    def configure_optimizers(self):\n",
    "        return torch.optim.AdamW(self.model.parameters(), lr=self.lr, weight_decay=1e-5)\n",
    "\n",
    "    def train_dataloader(self):\n",
    "        self.loader_l = len(trainloader)\n",
    "        return trainloader"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "GPU available: True, used: True\n",
      "TPU available: False, using: 0 TPU cores\n",
      "CUDA_VISIBLE_DEVICES: [0]\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "\n",
       "                Logging results to <a href=\"https://wandb.com\" target=\"_blank\">Weights & Biases</a> <a href=\"https://docs.wandb.com/integrations/jupyter.html\" target=\"_blank\">(Documentation)</a>.<br/>\n",
       "                Project page: <a href=\"https://app.wandb.ai/zymrael/torchdyn-toy_ffjord-bench\" target=\"_blank\">https://app.wandb.ai/zymrael/torchdyn-toy_ffjord-bench</a><br/>\n",
       "                Run page: <a href=\"https://app.wandb.ai/zymrael/torchdyn-toy_ffjord-bench/runs/sykodhbj\" target=\"_blank\">https://app.wandb.ai/zymrael/torchdyn-toy_ffjord-bench/runs/sykodhbj</a><br/>\n",
       "            "
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n",
      "  | Name  | Type       | Params\n",
      "-------------------------------------\n",
      "0 | model | Sequential | 1 K   \n",
      "/home/jyp/michael_dev/testenv/lib/python3.7/site-packages/pytorch_lightning/utilities/distributed.py:25: UserWarning: The dataloader, train dataloader, does not have many workers which may be a bottleneck. Consider increasing the value of the `num_workers` argument` (try 20 which is the number of cpus on this machine) in the `DataLoader` init to improve performance.\n",
      "  warnings.warn(*args, **kwargs)\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "491881fba94042cb8df50af7d3419476",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(FloatProgress(value=1.0, bar_style='info', description='Training', layout=Layout(flex='2'), max…"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    }
   ],
   "source": [
    "logger = WandbLogger(project='torchdyn-toy_ffjord-bench')\n",
    "learn = Learner(model)\n",
    "trainer = pl.Trainer(min_steps=10000, max_steps=10000, gpus=1, logger=logger)\n",
    "trainer.fit(learn);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [],
   "source": [
    "sample = prior.sample(torch.Size([1<<16]))\n",
    "# integrating from 1 to 0, 8 steps of rk4\n",
    "model[1].s_span = torch.linspace(1, 0, 2)\n",
    "new_x = model(sample).cpu().detach()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.collections.PathCollection at 0x7f82f8a8e2d0>"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 864x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(12, 4))\n",
    "plt.subplot(121)\n",
    "plt.scatter(new_x[:,1], new_x[:,2], s=0.3, c='blue')\n",
    "#plt.scatter(boh[:,0], boh[:,1], s=0.3, c='black')\n",
    "\n",
    "plt.subplot(122)\n",
    "plt.scatter(X[:,0], X[:,1], s=0.3, c='red')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "def cnf_density(model):\n",
    "    with torch.no_grad():\n",
    "        npts = 200\n",
    "        side = np.linspace(-2., 2., npts)\n",
    "        xx, yy = np.meshgrid(side, side)\n",
    "        memory= 100\n",
    "\n",
    "        x = np.hstack([xx.reshape(-1, 1), yy.reshape(-1, 1)])\n",
    "        x = torch.from_numpy(x).type(torch.float32).to(device)\n",
    "\n",
    "        z, delta_logp = [], []\n",
    "        inds = torch.arange(0, x.shape[0]).to(torch.int64)\n",
    "        for ii in torch.split(inds, int(memory**2)):\n",
    "            z_full = model(x[ii]).cpu().detach()\n",
    "            z_, delta_logp_ = z_full[:, 1:], z_full[:, 0]\n",
    "            z.append(z_)\n",
    "            delta_logp.append(delta_logp_)\n",
    "\n",
    "        z = torch.cat(z, 0)\n",
    "        delta_logp = torch.cat(delta_logp, 0)\n",
    "\n",
    "        logpz = prior.log_prob(z.cuda()).cpu() # logp(z)\n",
    "        logpx = logpz - delta_logp\n",
    "        px = np.exp(logpx.cpu().numpy()).reshape(npts, npts)\n",
    "        plt.imshow(px, cmap='inferno', vmax=px.mean());\n",
    "a = cnf_density(model)       "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "py37",
   "language": "python",
   "name": "py37"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.7"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}
